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chore: import upstream snapshot with attribution
2026-07-13 12:41:19 +08:00

73 lines
2.0 KiB
C++

// Copyright (c) ONNX Project Contributors
//
// SPDX-License-Identifier: Apache-2.0
#include <memory>
#include <string>
#include "gtest/gtest.h"
#include "onnx/common/ir.h"
#include "onnx/common/ir_pb_converter.h"
namespace ONNX_NAMESPACE {
namespace Test {
static bool IsValidIdentifier(const std::string& name) {
if (name.empty()) {
return false;
}
if (!isalpha(name[0]) && name[0] != '_') {
return false;
}
for (size_t i = 1; i < name.size(); ++i) {
if (!isalnum(name[i]) && name[i] != '_') {
return false;
}
}
return true;
}
TEST(IR, ValidIdentifierTest) {
Graph* g = new Graph(); // NOLINT(cppcoreguidelines-owning-memory)
g->setName("test");
Value* x = g->addInput();
x->setUniqueName("x");
x->setElemType(ONNX_NAMESPACE::TensorProto_DataType_FLOAT);
x->setSizes({Dimension("M"), Dimension("N")});
Node* node1 = g->create(kNeg, 1);
node1->addInput(x);
g->appendNode(node1);
Value* temp1 = node1->outputs()[0];
Node* node2 = g->create(kNeg, 1);
node2->addInput(temp1);
g->appendNode(node2);
Value* y = node2->outputs()[0];
g->registerOutput(y);
ModelProto model;
ExportModelProto(&model, std::shared_ptr<Graph>(g));
for (const auto& node : model.graph().node()) {
for (const auto& name : node.output()) {
EXPECT_TRUE(IsValidIdentifier(name));
}
}
}
// Regression test: Tensor::elem_num() and size_from_dim() must use 64-bit
// arithmetic. Previously, std::accumulate used `1` (int) as the initial value,
// causing 32-bit multiplication that silently overflowed for tensors whose
// element count exceeded INT_MAX (~2.1B). Fixed by using int64_t{1}.
TEST(Tensor, ElemNumLargeTensorNoOverflow) {
Tensor t;
// 50000 * 50000 = 2,500,000,000 which exceeds INT32_MAX (2,147,483,647)
t.sizes() = {50000, 50000};
const int64_t expected = static_cast<int64_t>(50000) * 50000;
EXPECT_EQ(t.elem_num(), expected);
EXPECT_EQ(t.size_from_dim(0), expected);
EXPECT_EQ(t.size_from_dim(1), int64_t{50000});
}
} // namespace Test
} // namespace ONNX_NAMESPACE